Quadro RTX 8000 vs RTX 3080

TuringvsAmpereUpdated 36 days ago

The RTX 3080 emerges as the winner for most cloud ML use cases. Its 29.8 TFLOPS compute doubles the Quadro RTX 8000's 16.3 TFLOPS, paired with $0.06 per hour pricing across eight offers, outweighing the 48 GB VRAM advantage for typical batch sizes fitting 10 to 12 GB.

Specifications Compared

SpecQUADRO-RTX-8000RTX-3080
TDP260W320W
VRAM48 GB10-12 GB
CUDA Cores4,6088,704
Memory TypeGDDR6GDDR6X
ArchitectureTuringAmpere
Form FactorsPCIePCIe
InterconnectNVLink
Tensor Cores576272
FP16 Performance16.3 TFLOPS29.8 TFLOPS
FP32 Performance16.3 TFLOPS29.8 TFLOPS
Memory Bandwidth672 GB/s760 GB/s

Performance Analysis

The RTX 3080 demonstrates superior raw compute with 29.8 TFLOPS in FP16 and FP32, nearly doubling the Quadro RTX 8000's 16.3 TFLOPS. This advantage accelerates deep learning training epochs and inference queries for models fitting within 10 to 12 GB VRAM, reducing time-to-result in tensor core-heavy operations.

Memory capacity defines key limits: the Quadro RTX 8000's 48 GB GDDR6 enables larger batch sizes in training large language models, minimizing data loading overhead compared to the RTX 3080's 10 to 12 GB GDDR6X. However, the RTX 3080's 760 GB/s bandwidth outperforms the 672 GB/s on the Quadro, supporting faster data transfers in bandwidth-bound inference scenarios.

Power draw reflects efficiency differences, with the RTX 3080 at 320W TDP versus 260W on the Quadro RTX 8000. Ampere's architecture yields better performance per watt for modern workloads, though NVLink on the Quadro aids scaled multi-GPU training.

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When to Choose the Quadro RTX 8000

The Quadro RTX 8000 suits memory-intensive applications exceeding 12 GB VRAM, such as training massive scientific simulations or large-scale 3D rendering. Its 48 GB capacity handles oversized datasets without splitting, and NVLink interconnect enables efficient multi-GPU communication.

Professionals in CAD or visualization workflows benefit from Turing's stability and 672 GB/s bandwidth for sustained loads.

When to Choose the RTX 3080

The RTX 3080 excels in cost-sensitive, high-throughput tasks like gaming, video rendering, or standard ML inference, available from $0.06 per hour. Its 29.8 TFLOPS performance and 760 GB/s bandwidth deliver faster results for models under 10 GB.

Cloud users prioritize Ampere's 2020 architecture for broader software support and eight live offers averaging $0.13 per hour.

Use Cases

LLM Training
Quadro RTX 8000

The Quadro RTX 8000's 48 GB VRAM supports larger models and batch sizes critical for LLM training, unlike the RTX 3080's 10 to 12 GB limit.

LLM Inference
RTX 3080

RTX 3080's 29.8 TFLOPS FP16 performance enables faster query throughput for inference serving compared to 16.3 TFLOPS on the Quadro RTX 8000.

Fine-tuning
Either

Fine-tuning smaller models fits within RTX 3080's 10 to 12 GB VRAM with 29.8 TFLOPS speed, while Quadro RTX 8000's 48 GB aids larger parameter sets.

Stable Diffusion
RTX 3080

Stable Diffusion pipelines run efficiently on RTX 3080's 760 GB/s bandwidth and 29.8 TFLOPS, generating images faster than the Quadro RTX 8000's 16.3 TFLOPS.

Scientific Computing
Quadro RTX 8000

Quadro RTX 8000's 48 GB VRAM and NVLink handle memory-heavy simulations, surpassing RTX 3080's 10 to 12 GB for complex datasets.

Frequently Asked Questions

Which GPU has more VRAM: Quadro RTX 8000 or RTX 3080?

The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, far exceeding the RTX 3080's 10 to 12 GB GDDR6X. This makes the Quadro better for large-model workloads. The RTX 3080 compensates with higher 760 GB/s bandwidth.

What is the FP32 performance difference between Quadro RTX 8000 and RTX 3080?

RTX 3080 achieves 29.8 TFLOPS in FP32, almost double the Quadro RTX 8000's 16.3 TFLOPS. This boosts training and inference speeds on the RTX 3080. Both match FP16 to FP32 ratios via tensor cores.

Does Quadro RTX 8000 support NVLink?

Yes, the Quadro RTX 8000 includes NVLink interconnect for multi-GPU scaling. The RTX 3080 lacks this feature. NVLink enhances bandwidth in professional clusters.

What are the cloud prices for RTX 3080?

RTX 3080 offers start at $0.06 per hour, averaging $0.13 per hour across eight live providers. Quadro RTX 8000 has no current live offers. This makes RTX 3080 more accessible.

Which has higher TDP: Quadro RTX 8000 or RTX 3080?

RTX 3080 draws 320W TDP, higher than Quadro RTX 8000's 260W. Ampere architecture improves performance per watt despite increased power. Cooling needs scale accordingly.

What architectures do these GPUs use?

Quadro RTX 8000 uses Turing from 2018, while RTX 3080 employs Ampere from 2020. Ampere delivers 29.8 TFLOPS versus Turing's 16.3 TFLOPS. Newer architecture supports advanced features.

Which is cheaper to rent, the Quadro RTX 8000 or the RTX 3080?

Cloud rental prices for both the Quadro RTX 8000 and RTX 3080 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.

How much VRAM does the Quadro RTX 8000 have compared to the RTX 3080?

The Quadro RTX 8000 has 48 GB of GDDR6 memory. The RTX 3080 has 10 to 12 GB of GDDR6X memory.

Can I find Quadro RTX 8000 and RTX 3080 GPUs available to rent right now?

Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.

What is the main difference between the Quadro RTX 8000 and the RTX 3080?

The Quadro RTX 8000 uses the Turing architecture (2018) while the RTX 3080 uses Ampere (2020). The RTX 3080 delivers 1.8x the FP16 throughput and 1.1x the memory bandwidth of the Quadro RTX 8000.

Quadro RTX 8000 vs RTX 3080: 48GB GDDR6 vs 12GB GDDR6X | GPUPerHour